Download Improving Precipitation Phase Determination through Air Mass

Improving Precipitation Phase Determination
through Air Mass Boundary Identification
SMHI Jan 2011
Feiccabrino James1, Lundberg Angela1, and David Gustafsson2
1Div.
of Geosciences, Dep. of Civil, Mining & Environmental Engineering & Geosciences, Luleå
University of Technology, Luleå, Sweden
2Department of Land and Water Resources Engineering, Royal Institute of Technology KTH,
Stockholm, Sweden
Accepted for publication in Hydrology Research
Introduction
Correct determination of precipitation phases is important for
estimates of snow storage in hydrological, regional and
global climate models.
Precipitation phase is especially critical for models
simulating forest processes since canopy storage capacity is
about one order of magnitude larger for snow than for rain.
Hydrological models that apply the same surface-air
temperature based precipitation phase identification scheme
for all types of precipitation events neglect the fact that
surface precipitation phase results from energy exchanges
between air in the lower atmosphere and the falling
precipitation.
Linear snow/rain threshold schemes
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Air temperature c)
a) one single surface air
temperature threshold (TR/S)
separating rain from snow
-1.00
0.00
1.00
2.00
3.00
•
one for all rain (TR)
•
linear decrease in snow
fraction in between
--
Snow fraction
b) two surface air temperature
thresholds,
• one for all snow (TS)
__
Snow fraction
-1,00
1,00
0,90
0,80
0,70
0,60
0,50
0,40
0,30
0,20
0,10
0,00
0,00
Alptal
Hyytiääla
UEB
1,00
2,00
Air temperature (C)
3,00
Large range in suggested relationships between
snow fraction and surface air temperature
1,0
Alptal
0,9
Hyytiääla
Berms
0,8
Hitsujigaoka
UEB
Snowfraction_
0,7
Frazer
0,6
LTU
0,5
0,4
0,3
0,2
0,1
0,0
-6
-5
-4
-3
-2
-1
0
1
Air temperature (C)
2
3
4
5
6
An Air Mass Boundary (AMB)…..
• Separates two air masses with different
characteristics e.g. one warm and one cold
Vertical air temp. profiles in the lower
troposphere for different near freezing
precipitation events
COLD
AIRMASS
WARM
AIRMASS
COLD
AIRMASS
WARM
AIRMASS
Melting
snow
a) Steadily cooling air temp. with height, without AMB
b) AMB separating a cold (under) and a warm (above) air mass,
c) AMB separating a warm (below) and a cold (above) air mass,
d) Steadily cooling air temp. with height interrupted by an isothermal layer due to
latent heat released when falling snow melts.
Vertical air temp. profiles in the lower
troposphere for different near freezing
precipitation events
Melting
snow
AMB = air mass boundary
a) Steadily cooling air temp. with height, without AMB
b) AMB separating a cold (under) and a warm (above) air mass,
ABOVE FREEZING
TEMPERATURE AIR
PRECIPITATION
MUST FALL
THROUGH
c) AMB separating a warm (below) and a cold (above) air mass,
d) Steadily cooling air temp. with height interrupted by an isothermal layer due to
latent heat released when falling snow melts.
Aim: To show that AMB identification can
improve precipitation phase classification
Objectives:
To use 20 years of manual precipitation observations
from 8 weather stations in northern US
•
•
•
to separate different AMB using surface meteorological observations
to identify AMB having different TR/S, TS, or TR value/s
to illustrate the improvement achieved by analyzing easily
identifiable Cold-air-mass boundary (CAMB) events separated from
non-CAMB events compared to when all events were analyzed
together
– the CAMB events were recognized by a rapid air temperature
decrease
Lower troposphere cross sections with stationary
surface locations progressing in time from …..
… A to E in a warm AMB
... A to D in a cold AMB
Method
Surface AMB passage can be identified by…
• high wind speeds
• changes in wind direction
• changes in surface air temperature
Type of Front or Trough Acronym
Change in
Wind
Wind Direction Speed
Change in
Temperature
Warm Front
Ana-Cold Front
Kata-Cold Front (Upper)
Kata-Cold Front (Lower)
Occlusion Front
Arctic/Barotropic Trough
WF
ACF/CAMB
CAMB
CAMB
Strong
Strong
Strong
Weak
High
Low
Low
Low
High
Increase (weak)
Decrease (strong)
Decrease (weak)
Decrease (strong)
Pre-Frontal Trough
CAMB
-
-
Decrease (-)
Bold font used for identified air mass types and the parameters used to identify them.
Location of used
US Air Force
Weather Stations
Note: Temperatures reported in integers
Precipitation classified as
snow for snow, groppel, and ice pellets,
freezing for freezing rain, & freezing drizzle,
rain for rain, and drizzle,
mixed for any combination of the above categories
AMB classification based on surface
meteorological observations
Example : Identification of Cold air mass boundary (CAMB)
If the surface air temperature two hours before an observation (Tt-2)
was at least 2°C warmer than during the observation (Tt) the
event was classified as a CAMB
If [(Tt −2 − Tt ) ≥ 2°C ] ,
Similar (more complex) relationships
were used to try to identify other AMB
Acronym
Change in
Wind Direction
Wind
Speed
Change in
Temperature
WF
ACF/CAMB
CAMB
CAMB
Strong
Strong
Strong
Weak
High
Low
Low
Low
High
Increase (weak)
Decrease (strong)
Decrease (weak)
Decrease (strong)
CAMB
-
-
Decrease (-)
Results: Identified AMB
Percentage of all precipitation events
GROUP
% OBS
AP
100%
CAMB
12%
ACF
1%
WF
1%
SYMBOL
Comment: Less strict requirements on change rates would have
produced larger percentages, e.g. for CAMB use of
• longer time periods
• smaller temperature changes
Air temperatures given in integers, so
changes <1ºC in TR/S, TS and TR could not
be directly detected
Therefore, when changes in TR/S was analyzed, an indirect way was
used to indicate if the TR/S was smaller or larger than the
determined integer TR/S- value by analyzing the amount of
misclassified precipitation.
Correct and incorrect classified
precipitation phase (%) for TR/S at 1°C.
Correct classified rain (■)
Misclassified rain (║)
Correct classified snow (□)
Misclassified snow (═)
Observed mixed precipitation (%) for
identified CAMB and non-CAMB.
Differences in rain vs snow plot depending
on how mixed precipitation is treated
Large divergence in snow fraction SF
between AMB
AP = all precipitation events
WF = warm fronts
ACF = Ana-cold fronts
CAMB = Cold air mass boundaries
Results
When a 2-hour requirement was used to separate CAMB and nonCAMB events the …
– TS and TR values (0°C; 4°C) for CAMB events were 1°C
warmer than for non-CAMB (-1°C; 3°C).
– (but the changes in TRS-values were < 1°C )
When CAMB and non-CAMB were analyzed separately, the
number of misclassified precipitation events was reduced by 23%.
Discussion
•
•
•
•
With air temperatures given in 0.1ºC differences in TR/S would
probably have been possible to identify.
Since CAMB often produces more precipitation than other
types of precipitation events, it is likely that the improvement in
misclassified precipitation would have been even larger if the
study hade been made on precipitation mass instead of on
number of events.
Other AMB might be identifiable at a finer temperature scale
and it would be interesting to check if other temperature
changes (2ºC) and time steps (t two h) would have produced
larger or smaller improvements.
Complications with a 24 hour time step…
•
•
Daily surface temperature variations due to diurnal variations in
cloudiness
– If clouds move in just after sunset after a warm day, heat is
trapped in the atmosphere overnight (may be mistaken for a
warm front)
– If clouds move in after cold night, chill is trapped in the
atmosphere (may be mistaken as a cold front).
So it will be more complex to avoid misinterpretation at the 24 hr
scale.
Difficulties with trying to develop a 24
hour time step
Need to overcome cooling and warming due to varying cloud and
fog conditions that are not associated with fronts (these should
not produce much precip).
However, 24 hr Temperature changes due to the time of day clouds
move over a location will effect this kind of analysis. If clouds
move in just after sunset, then more heat is trapped in the
atmosphere overnight (this may be mistaken for a warm front),
and vice versa with daytime temperatures being lower if clouds
move in after a full night of cooling (may be mistaken as a cold
front). So it will be more complex to avoid misinterpretation at
the 24 hr scale, not impossible, but it may be impracticle
Conclusions
•
•
•
•
•
A promising method to reduce the amount of misclassified
precipitation in hydrological models by separating
observations into AMB categories is presented.
All information used for this analysis is already available, no
new information has to be gathered
This separation can be done using easily identifiable
surface AMB characteristics such as surface air
temperature, wind speed and wind direction.
CAMB observations were identified by If [(Tt −2 − Tt ) ≥ 2°C ] ,
and were found to be 12% of all precipitation.
Analyzing CAMB separately from non-CAMB obs. reduced
the misclassified precipitation observations from 7% to 5.4%
(23%)